Accurate coding for the Hierarchical Condition Category (HCC) model is vital to healthcare organizations’ reimbursements. Poor coding can result in costly audits and financial penalties.
Implementing a series of best practices for HCC risk adjustment coding documentation is essential to avoid costly errors. These steps can help your team improve clinical documentation and ensure accurate coding.
Documentation is Key
Health plans should always focus on accurate coding and documentation, as this impacts member health outcomes and reimbursement. The Medicare HCC model is value-based, and the more precise a health plan’s coding, the more compensation it receives for taking care of its members. Health plans must have a defined process to identify and correct errors that lead to under or over-reporting risk scores. It is typically done through a manual, time-consuming process that involves reviewing claims data regularly to identify any issues with coding.
A health plan’s coding review processes should be able to detect coding errors and work with providers to ensure that all documentation is correct and complete. It helps reduce the number of erroneous codes assigned, which can lead to inaccurate HCC risk adjustment coding and a reduction in revenue.
Use a specialized risk adjustment code review & audit solution that employs natural language processing to identify and fix errors to ensure your coding is current. This tool can help streamline the coding process, improve efficiency, and increase accuracy by identifying potential coding errors in medical records. It’s also a good idea for health plans to train their staff on proper coding practices, which can help to ensure compliance and reduce coding gaps.
Educate Your Staff
Hierarchical Condition Category (HCC) coding is increasingly important in determining accurate reimbursement as the healthcare industry shifts to value-based care. Proper coding helps to optimize revenue for Medicare Advantage (MA) plans and other healthcare payers while providing patients better care.
One of the most effective ways to improve coding performance is through educational programs that provide clinicians with specific HCC documentation guidelines. In addition to educational programs, it is also critical that coders are provided with the tools they need to perform their jobs efficiently and effectively. It can be achieved through integrating documentation and coding aids within EHR systems to prompt physicians and help them document accurately.
Another key to ensuring accurate coding is establishing a comprehensive process for reviewing claims before submission. It can be accomplished through a combination of review methods, including interdisciplinary workgroups of clinical and administrative members. It ensures that the coding and medical records are reviewed holistically, eliminating errors from using only one data source.
HCC coding is a complex process that requires vigilance and attention to detail. When errors are made, it can cost a health plan millions of dollars. By implementing these best practices, payers can increase HCC coding accuracy, resulting in more accurate per-member cost calculations and better provider compensation.
Utilize NLP-Powered Retrospective Chart Review Solutions
As healthcare organizations shift to value-based care, HCC coding accuracy is more critical than ever. However, implementing a robust risk adjustment coding program requires time and resources. Fortunately, several technological solutions can simplify and streamline the process. These tools can also help ensure compliance and accuracy of HCC coding, thereby improving reimbursement and overall clinical outcomes.
HCC (Hierarchical Condition Categories) risk adjustment coding calculates each patient’s Medicare Advantage risk score. This score is then used to establish capitation payments for the MA plan. The more at-risk the patient is, the higher the MA plan’s costs are. CMS defines 70 disease burden categories correlated to specific diagnosis codes. The diagnoses are reported on each encounter, and the risk adjustment model resets yearly.
While accurate coding and documentation are necessary to ensure proper risk adjustment coding, the reality is that many health plans struggle with this issue due to changing guidelines, coding updates, and changes in the patient’s health status.
To combat these challenges, medical coding service providers and healthcare organizations can utilize technology solutions to automate risk adjustment workflows and improve their coding and documentation performance. It uses advanced deep Knowledge Graph-based Natural Language Processing to read charts as human coders do and then suggests appropriate risk adjustment codes.
Automate Your Processes
When it comes to risk adjustment coding, human error is more common than you might think. A missed code can impact Medicare Advantage members, revenue, operations, and regulatory compliance. When you add that Medicare Advantage plans are under constant scrutiny and risk of a RADV audit, your processes and tools must have a strong foundation for accuracy.
That’s where a robust QA strategy and automated software come into play. Whether for redaction purposes or to help limit upcoding (when codes are pushed higher than documented), strong HCC coding QA workflows should be part of your overall risk adjustment management plan.
Having the right software in place can make or break your ability to accurately capture HCC codes and ensure compliance. A risk adjustment coding tool that can support audit workflows and provide the flexibility to respond to regulatory changes quickly is crucial to ensuring your team’s success in this fast-paced landscape.
With the RADV final rule on the horizon and continued pressure to maximize reimbursement under value-based care, it’s more important than ever that your organization have an accurate, effective risk adjustment coding strategy in place. By following these six best practices, you can ensure compliance and accuracy in your coding and documentation.
With the right combination of provider education, advanced EHR tools, streamlined workflows, and NLP-powered retrospective chart review solutions, you can get ahead of the curve on your RADV audit and avoid penalties from CMS.